The following account of the prior art relates to one of the areas of application of the present application, hearing aids.
Acoustic feedback occurs because the output loudspeaker signal from an audio system providing amplification of a signal picked up by a microphone is partly returned to the microphone via an acoustic coupling through the air or other media. The part of the loudspeaker signal returned to the microphone is then re-amplified by the system before it is re-presented at the loudspeaker, and again returned to the microphone. As this cycle continues, the effect of acoustic feedback becomes audible as artifacts or even worse, howling, when the system becomes unstable. The problem appears typically when the microphone and the loudspeaker are placed closely together (or if the amplification of the microphone signal is large), as e.g. in hearing aids or other audio systems. Some other classic situations with feedback problem are telephony, public address systems, headsets, audio conference systems, etc. Frequency dependent acoustic, electrical and mechanical feedback identification methods are commonly used in hearing devices, in particular hearing instruments, to ensure their stability. Unstable systems due to acoustic feedback tend to significantly contaminate the desired audio input signal with narrow band frequency components, which are often perceived as howl or whistle.
During fitting and/or during normal operation of a hearing aid, an important task is to measure the static feedback path from the hearing aid receiver to microphone. This feedback path measurement can e.g. be used to determine the maximum allowed gain in hearing aids to avoid the problem of acoustic feedback (howl). A method of measuring critical gain is e.g. described in US2011026725A1, wherein an estimate of the surrounding noise level relative to an acceptable threshold value is provided.
Often, the occurrence of feedback howling or other feedback artifacts in hearing aids is due to a sub-optimal fitting of the hearing aid, or because the amplification is too high for the (on-board) hearing aid feedback management system to handle.
Typically, the hearing aid fitting is performed with an acoustic feedback condition that is easy to handle for the hearing aid feedback management system. The feedback management system may in practice face much more challenging situations, when the acoustic feedback condition becomes more complicated, such e.g. as when the user puts on a hat or have a telephone next to his/her ear.
In current hearing aid systems, a gain reduction is typically applied in challenging feedback situations. However, it is often unknown, how large a gain reduction is necessary (to just prevent howling). A (rough) estimate may be provided from calculated estimates of a current feedback path or loop gain, but such estimates are typically not very reliable in challenging feedback situations. Hence, a larger-than-needed gain reduction is often applied (to be on the safe side).
The acoustic feedback measurement of a hearing aid can be easily carried out by playing a probe signal, e.g. a stochastic signal such as white noise (WN) or colored noise, through the hearing aid receiver (loudspeaker), where the hearing aid microphone signal is recorded at the same time. Based on these two signal sequences, an estimate of the unknown feedback path can be determined, using for example an adaptive algorithm. A frequently used adaptive algorithm in state of the art hearing aid systems is a normalized least mean square (NLMS) algorithm. Other algorithms may be used, see e.g. [Haykin; 2001].
Other signals such as a chirp signal (sine-sweep) or sinusoids (sine-waves) can also be used as probe signals. These different probe signals would, however, lead to different properties of the feedback path estimation. In hearing aid applications, the most relevant properties are the convergence rate (indicating how long the measurement takes), and the steady-state error (how precise would the estimated feedback path be).
The noise based methods have relatively slow convergence rates, meaning that dispensers and hearing aid users have to spend a relatively long time waiting on acoustic feedback measurements. Thus, there is a need to shorten the required measurement time, which may be of the order of 15 seconds. Long measurement times (long convergence times of the adaptive algorithm) are often a consequence of noisy measurement environments.
The chirp signal based measurement is generally faster, but it is much more demanding in computational power, which makes this approach unrealistic in state-of-the-art hearing aids. Measurements based on sinusoids have a very fast convergence rate, but it can only provide feedback path estimation at selected frequencies.
WO 02/093854 A1 describes the use of perfect sequences to estimate an impulse response of a transmission channel. It is known that perfect sequences (PSEQ) and perfect sweep (PSweep) sequences can be used to improve the convergence rate of an NLMS algorithm, cf. e.g. [Antweiler & Enzner; 2009] and [Antweiler et al.; 2012], respectively.
During fitting of a hearing aid to a particular user's needs, a feedback measurement is typically performed by using the feedback cancellation system of the hearing aid configured in a specific fitting-mode. A limitation of this procedure is that the feedback cancellation system in hearing aids is implemented in a specific way (adapted to its normal use in the hearing aid), and it offers very often only limited estimation accuracy and a lengthy measurement time is required.